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Review How DBMS physically organizes data Different file organizations or access methods Record formats Page Formats What is Indexing? Different indexing.

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Presentation on theme: "Review How DBMS physically organizes data Different file organizations or access methods Record formats Page Formats What is Indexing? Different indexing."— Presentation transcript:


2 Review How DBMS physically organizes data Different file organizations or access methods Record formats Page Formats What is Indexing? Different indexing methods How to create indexes using SQL

3 DBMS has to store data somewhere Choices: Main memory Expensive – compared to secondary and tertiary storage Fast – in memory operations are fast Volatile – not possible to save data from one run to its next Used for storing current data Secondary storage (hard disk) Less expensive – compared to main memory Slower – compared to main memory, faster compared to tapes Persistent – data from one run can be saved to the disk to be used in the next run Used for storing the database Tertiary storage (tapes) Cheapest Slowest – sequential data access Used for data archives

4 This means that data needs to be read from the hard disk into memory (RAM) Written from the memory onto the hard disk Because I/O disk operations are slow query performance depends upon how data is stored on hard disks The lowest component of the DBMS performs storage management activities Other DBMS components need not know how these low level activities are performed

5 A disk is organized into a number of blocks or pages A page is the unit of exchange between the disk and the main memory A collection of pages is known as a file DBMS stores data in one or more files on the hard disk

6 Database tables are made up of one or more tuples (rows) Each tuple has one or more attributes One or more tuples from a table are written into a page on the hard disk Larger tuples may need more than one page! Tuples on the disk are known as records Records are separated by record delimiter Attributes on the hard disk are known as fields Fields are separated by field delimiter

7 Page : abstraction is used for I/O Record : data granularity for higher level of DBMS How to arrange records in pages? Identify a record:, where slot_number = rid Most cases, use as rid. Alternative approaches to manage slots on a page How to support insert/deleting/searching?

8 Information about field types same for all records in a file Stored record format in system catalogs. + Finding ith field does not require scan of record, just offset calculation. Base address (B) L1L2L3L4 F1F2F3F4 Address = B+L1+L2

9 * Record id =. * Note: In first alternative, moving records for free space management changes rid; may not be acceptable if existing external references to the record that is moved. Slot 1 Slot 2 Slot N... N M1 0 M PACKED UNPACKED, BITMAP Slot 1 Slot 2 Slot N Free Space Slot M 11 number of records number of slots

10 Two alternative formats (# fields is fixed): + Second offers direct access to ith field + efficient storage of nulls ; - small directory overhead. 4$$$$ Field Count Fields Delimited by Special Symbols F1 F2 F3 F4 Array of Field Offsets

11 * Slot directory = { } Page i Rid = (i,N) Rid = (i,2) Rid = (i,1) Pointer to start of free space SLOT DIRECTORY N N # slots Offset of record from start of data area Length = 24 Length = 16 Length = 20

12 * Slot directory = { } * Dis/Advantages: + Moving: rid is not changed + Deletion: offset = -1 (rid changed? Can we delete slot? Why?) + Insertion: Reuse deleted slot. Only insert if none available. * Free space? Free space pointer? Recycle after deletion?

13 Meta information stored in system catalogs. For each index: structure (e.g., B+ tree) and search key fields For each relation: name, file name, file structure (e.g., Heap file) attribute name and type, for each attribute index name, for each index integrity constraints For each view: view name and definition Plus statistics, authorization, buffer pool size, etc. * Catalogs are themselves stored as relations !



16 The physical arrangement of data in a file into records and pages on the disk File organization determines the set of access methods for Storing and retrieving records from a file Therefore, file organization synonymous with access method We study three types of file organization Unordered or Heap files Ordered or sequential files Hash files We examine each of them in terms of the operations we perform on the database Insert a new record Search for a record (or update a record) Delete a record

17 Records are stored in the same order in which they are created Insert operation Fast – because the incoming record is written at the end of the last page of the file Search (or update) operation Slow – because linear search is performed on pages Delete Operation Slow – because the record to be deleted is first searched for Deleting the record creates a hole in the page Periodic file compacting work required to reclaim the wasted space

18 Records are sorted on the values of one or more fields Ordering field – the field on which the records are sorted Ordering key – the key of the file when it is used for record sorting Search (or update) Operation Fast – because binary search is performed on sorted records Update the ordering field? Delete Operation Fast – because searching the record is fast Periodic file compacting work is, of course, required Insert Operation Poor – because if we insert the new record in the correct position we need to shift all the subsequent records in the file Alternatively an overflow file is created which contains all the new records as a heap Periodically overflow file is merged with the main file If overflow file is created search and delete operations for records in the overflow file have to be linear!

19 Is an array of buckets Given a record, r a hash function, h(r) computes the index of the bucket in which record r belongs h uses one or more fields in the record called hash fields Hash key - the key of the file when it is used by the hash function Example hash function Assume that the staff last name is used as the hash field Assume also that the hash file size is 26 buckets - each bucket corresponding to each of the letters from the alphabet Then a hash function can be defined which computes the bucket address (index) based on the first letter in the last name.

20 Insert Operation Fast – because the hash function computes the index of the bucket to which the record belongs If that bucket is full you go to the next free one Search Operation Fast – because the hash function computes the index of the bucket Performance may degrade if the record is not found in the bucket suggested by hash function Delete Operation Fast – once again for the same reason of hashing function being able to locate the record quick

21 Can we do anything else to improve query performance other than selecting a good file organization? Yes, the answer lies in indexing Index - a data structure that allows the DBMS to locate particular records in a file more quickly Very similar to the index at the end of a book to locate various topics covered in the book Types of Index Primary index – one primary index per file Clustering index – one clustering index per file – data file is ordered on a non-key field and the index file is built on that non- key field Secondary index – many secondary indexes per file Sparse index – has only some of the search key values in the file Dense index – has an index corresponding to every search key value in the file

22 The data file is sequentially ordered on the key field Index file stores all (dense) or some (sparse) values of the key field and the page number of the data file in which the corresponding record is stored B0021 B0031 B0042 B0052 B0073 Branch B002 record Branch B003 record Branch B004 record Branch B005 record Branch B007 record Branch BranchNoStreetCityPostcode B00256 Clover DrLondonNW10 6EU B Main StGlasgowG11 9QX B00432 Manse RdBristolBS99 1NZ B00522 Deer RdLondonSW1 4EH B00716 Argyll StAberdeenAB2 3SU

23 ISAM – Indexed sequential access method is based on primary index Default access method or table type in MySQL, MyISAM is an extension of ISAM Insert and delete operations disturb the sorting You need an overflow file which periodically needs to be merged with the main file

24 An index file that uses a non primary field as an index e.g. City field in the branch table They improve the performance of queries that use attributes other than the primary key You can use a separate index for every attribute you wish to use in the WHERE clause of your select query But there is the overhead of maintaining a large number of these indexes

25 You can create an index for every table you create in SQL For example CREATE INDEX branchNoIndex on branch(branchNo); CREATE INDEX numberCityIndex on branch(branchNo,city); DROP INDEX branchNoIndex;

26 Disks provide cheap, non-volatile storage. Random access, but cost depends on location of page on disk Important to arrange data sequentially to minimize seek and rotation delays. Buffer manager brings pages into RAM. Page stays in RAM until released by requestor. Written to disk when frame chosen for replacement. Frame to replace based on replacement policy. Tries to pre-fetch several pages at a time.

27 DBMS vs. OS File Support DBMS needs features not found in many OSs. forcing a page to disk controlling the order of page writes to disk files spanning disks ability to control pre-fetching and page replacement policy based on predictable access patterns Formats for Records and Pages : Slotted page format : supports variable length records and allows records to move on page. Variable length record format : field offset directory offers support for direct access to ith field and null values.

28 File layer keeps track of pages in a file, and supports abstraction of a collection of records. Pages with free space identified using linked list or directory structure Indexes support efficient retrieval of records based on the values in some fields. Catalog relations store information about relations, indexes and views. Information common to all records in collection.

29 File organization or access method determines the performance of search, insert and delete operations. Access methods are the primary means to achieve improved performance Index structures help to improve the performance further More index structures in the next lecture

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